Characterization of rare earth minerals extraction flowsheet with x-ray microanalysis at high spatial resolution

Rare earth elements (REE) become increasingly significant for renewable energy devices and high-tech electronic products because of their large-scale popularization and applications. Nechalacho rare earth deposit is an important REE source in the world and an ideal setting to investigate the rare earth minerals (REM) evolution. Qualitative description of mineralogy and quantitative measurement of composition and texture are both important for the optimization of mineral processing. However, most of the widely industrially applied techniques have the problems of low spatial resolution and global analysis, which result in the omission and misidentification of small features. The aim of this work is to characterize REM in Nechalacho deposit with high spatial resolution and high count rate SEM/EDS system and assisting to find the optimal extraction flowsheet.In this work, two field emission SEM and one tungsten emission VP-SEM were utilized to characterize the composition and distribution of REM. X-ray microanalysis was achieved by the conventional silicon drift detector (SDD) with 80 mm2 collecting area located on the side of specimen and an annular SDD inserted below the objective lens. f-ratio method and phase map transformed from EDS elemental map were applied to acquire the compositional information and to characterize the REM distribution. Two methods (manual and automatic) of processing phase map were presented and discussed, demonstrating the phase changes through REM separation stages. The high spatial resolution and high count rate of field emission SEM allow phase identification at a small scale. The annular detector differentiated Zr-bearing phases and Y-bearing phases at a micron-scale successfully. Tungsten emission VP-SEM allows the characterization on a sample without a good conductivity, simplifying the mineral sample preparation. The standardless f-ratio method is proved to be a more effective way to judge the sample homogeneity and can provide higher compositional contrast in a quantitative element map. Python scripts and Aztec software were used to obtain phase map for evaluating the effectivity of each REM separation stage and determining the best fraction for recovering REM. Compared with the automatic software, Python script method is more accurate, reliable, and applicable for satisfying different requirements.Les terres rares sont au centre de la fabrication de produits technologique de pointe, tel que des batteries, turbines, et autres appareils électriques. Le gisement de terres rares Nechalago est une importante source pour l'approvisionnement mondial de ces éléments, ce qui en fait un candidat idéal pour l'étude de l'évolution géologique de tels gisements de minéraux de terres rares. Décrire la composition et la texture cristallographique de ces minéraux de façons qualitative et quantitative est nécessaire à l'optimisation du procéder d'extraction métallurgique. Cependant, la plupart des techniques de caractérisation actuellement employé en contexte industriel sont limités en termes de résolution spatiale et d'analyse globales. Le but de ce travail est de caractériser les minéraux de terres rares du gisement de Nechalago avec une grande résolution spatial et avec un grand nombre de rayon X avec un system d'analyse dispersive en énergie dans un microscope électronique à balayage, dans le but d'optimiser l'extraction de minéraux de valeurs. Au cœur de ce travail, deux microscopes équipé de cannons a émission de champ à froid, et un microscope a pression variable équipé d'un canon à émission thermoïonique au tungstène et leurs détecteurs d'analyse dispersive en énergie ont été mis à contribution. Deux méthodes de traitement de données, manuelle et automatisée, ont été utilisées pour produire les cartes de phases présentées dans ce travail.La haute résolution spatiale et la rapidité de collection de microscopes à balayage à champs froid permettent l'identification de phases minéralurgique de façon très localisée. Le détecteur annulaire différencie les phases contenant du zircon de celles contenant de l'yttrium. Le microscope à émission thermoïnique au tungstène et à pression variable permet la caractérisation chimique d'échantillons peu conducteurs, ce qui simplifie la préparation d'échantillons. La caractérisation sans standards par f-ratio est une méthode efficace pour évaluer l'homogénéité d'un échantillon. Des scripts Python ainsi que le logiciel Aztec sont utilisés pour générer des cartes de phases. Ces cartes permettent d'évaluer la performance de chaque stade de la séparation des minéraux à terres rares et d'évaluer la meilleure route d'extraction. Le script Python est plus efficace, fiable et flexible pour différents usages

Multivariate Statistical Analysis on a SEM/EDS Phase Map of Rare Earth Minerals

The scanning electron microscope/X-ray energy dispersive spectrometer (SEM/EDS) system is widely applied to rare earth minerals (REMs) to qualitatively describe their mineralogy and quantitatively determine their composition. The performance of multivariate statistical analysis on the EDS raw dataset can enhance the efficiency and the accuracy of phase identification. In this work, the principal component analysis (PCA) and the blind source separation (BSS) algorithms were performed on an EDS map of a REM sample, assisting to achieve an efficient phase map analysis. The PCA significantly denoised the phase map and was used as a preprocessing step for the following BSS. The BSS separated the mixed EDS signals into a set of physically interpretable components, bringing convenience to the phase separation and identification. Through the comparison between the independent component analysis (ICA) and the nonnegative matrix factorization (NMF) algorithms, the NMF was confirmed to be more suitable for the EDS mapping analysis

Super-resolution imaging of synaptic and extra-synaptic AMPA receptors with Different-Sized fluorescent probes

Previous studies tracking AMPA receptor (AMPAR) diffusion at synapses observed a large mobile extrasynaptic AMPAR pool. Using super-resolution microscopy, we examined how fluorophore size and photostability affected AMPAR trafficking outside of, and within, post-synaptic densities (PSDs) from rats. Organic fluorescent dyes (≈ 4 nm), quantum dots, either small (≈ 10 nm diameter; sQDs) or big (>20 nm; bQDs), were coupled to AMPARs via different-sized linkers. We find that >90% of AMPARs labeled with fluorescent dyes or sQDs were diffusing in confined nanodomains in PSDs, which were stable for 15 min or longer. Less than 10% of sQD-AMPARs were extrasynaptic and highly mobile. In contrast, 5-10% of bQD-AMPARs were in PSDs and 90-95% were extrasynaptic as previously observed. Contrary to the hypothesis that AMPAR entry is limited by the occupancy of open PSD ‘slots’, our findings suggest that AMPARs rapidly enter stable ‘nanodomains’ in PSDs with lifetime ≥15 min, and do not accumulate in extrasynaptic membranes